Exploratory Data Analysis
## Warning: Missing column names filled in: 'X1' [1]
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## X1 = col_double(),
## Time = col_double(),
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## `756883` = col_double(),
## `842297` = col_double(),
## `842298` = col_double(),
## `842301` = col_double()
## )
## Warning: Missing column names filled in: 'X1' [1]
## Parsed with column specification:
## cols(
## X1 = col_double(),
## Time = col_double(),
## `601143` = col_double(),
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## )
## # A tibble: 1 x 11
## r.squared adj.r.squared sigma statistic p.value df logLik AIC BIC
## <dbl> <dbl> <dbl> <dbl> <dbl> <int> <dbl> <dbl> <dbl>
## 1 0.632 0.614 7.64 36.1 5.84e-6 2 -78.3 163. 166.
## # … with 2 more variables: deviance <dbl>, df.residual <int>
## # A tibble: 1 x 11
## r.squared adj.r.squared sigma statistic p.value df logLik AIC BIC
## <dbl> <dbl> <dbl> <dbl> <dbl> <int> <dbl> <dbl> <dbl>
## 1 0.636 0.619 7.59 36.7 5.15e-6 2 -78.2 162. 166.
## # … with 2 more variables: deviance <dbl>, df.residual <int>
## # A tibble: 1 x 11
## r.squared adj.r.squared sigma statistic p.value df logLik AIC BIC
## <dbl> <dbl> <dbl> <dbl> <dbl> <int> <dbl> <dbl> <dbl>
## 1 0.603 0.584 7.93 31.9 1.33e-5 2 -79.2 164. 168.
## # … with 2 more variables: deviance <dbl>, df.residual <int>
## # A tibble: 1 x 11
## r.squared adj.r.squared sigma statistic p.value df logLik AIC BIC
## <dbl> <dbl> <dbl> <dbl> <dbl> <int> <dbl> <dbl> <dbl>
## 1 0.575 0.555 8.21 28.4 2.76e-5 2 -80.0 166. 169.
## # … with 2 more variables: deviance <dbl>, df.residual <int>
## # A tibble: 1 x 11
## r.squared adj.r.squared sigma statistic p.value df logLik AIC BIC
## <dbl> <dbl> <dbl> <dbl> <dbl> <int> <dbl> <dbl> <dbl>
## 1 0.588 0.568 12.1 29.9 1.99e-5 2 -88.9 184. 187.
## # … with 2 more variables: deviance <dbl>, df.residual <int>
## # A tibble: 1 x 11
## r.squared adj.r.squared sigma statistic p.value df logLik AIC BIC
## <dbl> <dbl> <dbl> <dbl> <dbl> <int> <dbl> <dbl> <dbl>
## 1 0.578 0.558 12.2 28.7 2.57e-5 2 -89.2 184. 188.
## # … with 2 more variables: deviance <dbl>, df.residual <int>
## # A tibble: 1 x 11
## r.squared adj.r.squared sigma statistic p.value df logLik AIC BIC
## <dbl> <dbl> <dbl> <dbl> <dbl> <int> <dbl> <dbl> <dbl>
## 1 0.574 0.553 12.3 28.3 2.85e-5 2 -89.3 185. 188.
## # … with 2 more variables: deviance <dbl>, df.residual <int>
## # A tibble: 1 x 11
## r.squared adj.r.squared sigma statistic p.value df logLik AIC BIC
## <dbl> <dbl> <dbl> <dbl> <dbl> <int> <dbl> <dbl> <dbl>
## 1 0.603 0.584 11.9 31.9 1.32e-5 2 -88.5 183. 186.
## # … with 2 more variables: deviance <dbl>, df.residual <int>
## # A tibble: 1 x 11
## r.squared adj.r.squared sigma statistic p.value df logLik AIC BIC
## <dbl> <dbl> <dbl> <dbl> <dbl> <int> <dbl> <dbl> <dbl>
## 1 0.0431 -0.00478 0.162 0.900 0.354 2 9.94 -13.9 -10.6
## # … with 2 more variables: deviance <dbl>, df.residual <int>
## # A tibble: 1 x 11
## r.squared adj.r.squared sigma statistic p.value df logLik AIC BIC
## <dbl> <dbl> <dbl> <dbl> <dbl> <int> <dbl> <dbl> <dbl>
## 1 0.000706 -0.0493 0.165 0.0141 0.907 2 9.46 -12.9 -9.65
## # … with 2 more variables: deviance <dbl>, df.residual <int>